In linear algebra, the transpose of a matrix
A is another matrix AT (also written A′, Atr,tA
or At) created by any one of the following equivalent
actions:

reflect A over its main diagonal (which runs from top-left to
bottom-right) to obtain AT

write the rows of A as the columns of AT

write the columns of A as the rows of AT

Formally, the ith row, jth column element of
AT is the jth row, ith column element of
A:

[AT]i j = [A]j i

If A is an m × n matrix then
AT is an n × m
matrix.

You have been given a matrix as a 2D list with integers.
Your task is to return a transposed matrix based on input.

Input: A matrix as a list of lists with integers.

Output: The transposed matrix as a list/tuple of lists/tuples with integers.

Example:

checkio([[1, 2, 3],
[4, 5, 6],
[7, 8,...

The most obvious use for this idea is in mathematical software,
but the concept can be applied in the area of vector graphics.
On a computer, one can often avoid explicitly transposing a matrix in memory by simply accessing the same data in a different order.

0 < len() < 10
all(0 < len(row) < 10 for row in )

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